Schematic of the pixelwise binary cross-entropy loss function used to train the segmentation and tracking models. by Owen M. O’Connor (11965460)

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Utilizing variable background weight maps for training the model on debris. by Owen M. O’Connor (11965460)

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Loss history of segmentation model trained over 600 epochs. by Owen M. O’Connor (11965460)

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Low- and high-level subspace noise for the reverse-correlation of visual and audio stimuli. by Juan José Burred (6555578)

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Schematic showing how the tracking model uses the inputs to make predictions. by Owen M. O’Connor (11965460)

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Overview of MCell4 API generator. by Adam Husar (18437351)

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SCADET algorithm parameter configuration (Python implementation). by Xiaolong Zhang (470454)

Representative schematic of the geometric configuration used for a 120 electrode MEA. by Christopher S. Dunham (12239618)

Python implementation of a wildfire propagation example using m:n-CAk over Z and R. by Pau Fonseca i Casas (9507338)

“…</p><p dir="ltr"><br></p><p dir="ltr">## Files in the Project</p><p dir="ltr"><br></p><p dir="ltr">### Python Scripts</p><p dir="ltr">- **Wildfire_on_m_n-CAk.py**: This file contains the main code for the fire cellular automaton. …”

Poster: PyGMT: Accessing the Generic Mapping Tools from Python by Leonardo Uieda (97471)

“…We are using this bridge to develop PyGMT (<a href="http://www.pygmt.org/" rel="nofollow">www.pygmt.org</a>; formerly GMT/Python), an open-source library that allows users of the Python programming language to leverage the almost thirty years of continuous GMT development. …”

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”

Re-Implementation of Refactory_GPT_Models Tool by Aqsa Shabbir (18604261)

“…The file `requirements.txt` lists the python packages, along with their specific version number, required by the tool.…”

Code interpreter with LLM. by Jin Lu (428513)

“…We evaluated our proposed system on five educational datasets—AI2_ARC, OpenBookQA, E-EVAL, TQA, and ScienceQA—which represent diverse question types and domains. Compared to vanilla Large Language Models (LLMs), our approach combining Retrieval-Augmented Generation (RAG) with Code Interpreters achieved an average accuracy improvement of 10−15 percentage points. …”

Running times of equivalent programs based on <i>TextFormats</i> or other libraries, implemented in Nim, Python, and C. by Giorgio Gonnella (6670052)

OptiTools workflow. by Mehmet Akdel (11507114)

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In blue-red gradient, annual variation in geospatial clustering of average individual payments per zip code, with hatched overlay representing statistical significance. by Raphael E. Cuomo (9306269)

Comparison of the performance of the proposed tool with other commonly used tools for animal tracking. by Luc Nicolas Stiemer (17027735)

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

“…In recent years, manual model tuning has been gradually replaced by automated parameter search using a variety of different tools and methods. …”

Procedure for aligning the NeuroRat head model underlying the FEM simulations with the BBP circuit model. by Joseph James Tharayil (21416715)

Genomic view of archaeal and bacterial diversity in skeleton of coral Porites lutea and Isopora palifera by Kshitij Tandon (9398705)

“…From inner to outer ring, Innermost circle represents MAGs color coded at bacterial class level. …”